mirror of
https://github.com/hwchase17/langchain.git
synced 2025-08-23 11:32:10 +00:00
a0c2281540
```python
"""python scripts/update_mypy_ruff.py"""
import glob
import tomllib
from pathlib import Path
import toml
import subprocess
import re
ROOT_DIR = Path(__file__).parents[1]
def main():
for path in glob.glob(str(ROOT_DIR / "libs/**/pyproject.toml"), recursive=True):
print(path)
with open(path, "rb") as f:
pyproject = tomllib.load(f)
try:
pyproject["tool"]["poetry"]["group"]["typing"]["dependencies"]["mypy"] = (
"^1.10"
)
pyproject["tool"]["poetry"]["group"]["lint"]["dependencies"]["ruff"] = (
"^0.5"
)
except KeyError:
continue
with open(path, "w") as f:
toml.dump(pyproject, f)
cwd = "/".join(path.split("/")[:-1])
completed = subprocess.run(
"poetry lock --no-update; poetry install --with typing; poetry run mypy . --no-color",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
logs = completed.stdout.split("\n")
to_ignore = {}
for l in logs:
if re.match("^(.*)\:(\d+)\: error:.*\[(.*)\]", l):
path, line_no, error_type = re.match(
"^(.*)\:(\d+)\: error:.*\[(.*)\]", l
).groups()
if (path, line_no) in to_ignore:
to_ignore[(path, line_no)].append(error_type)
else:
to_ignore[(path, line_no)] = [error_type]
print(len(to_ignore))
for (error_path, line_no), error_types in to_ignore.items():
all_errors = ", ".join(error_types)
full_path = f"{cwd}/{error_path}"
try:
with open(full_path, "r") as f:
file_lines = f.readlines()
except FileNotFoundError:
continue
file_lines[int(line_no) - 1] = (
file_lines[int(line_no) - 1][:-1] + f" # type: ignore[{all_errors}]\n"
)
with open(full_path, "w") as f:
f.write("".join(file_lines))
subprocess.run(
"poetry run ruff format .; poetry run ruff --select I --fix .",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
if __name__ == "__main__":
main()
```
60 lines
2.3 KiB
Python
60 lines
2.3 KiB
Python
"""Python agent."""
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from typing import Any, Dict, Optional
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from langchain.agents.agent import AgentExecutor, BaseSingleActionAgent
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from langchain.agents.mrkl.base import ZeroShotAgent
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from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
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from langchain.agents.types import AgentType
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from langchain.chains.llm import LLMChain
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from langchain_core.callbacks.base import BaseCallbackManager
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from langchain_core.language_models import BaseLanguageModel
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from langchain_core.messages import SystemMessage
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from langchain_experimental.agents.agent_toolkits.python.prompt import PREFIX
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from langchain_experimental.tools.python.tool import PythonREPLTool
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def create_python_agent(
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llm: BaseLanguageModel,
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tool: PythonREPLTool,
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agent_type: AgentType = AgentType.ZERO_SHOT_REACT_DESCRIPTION,
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callback_manager: Optional[BaseCallbackManager] = None,
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verbose: bool = False,
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prefix: str = PREFIX,
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agent_executor_kwargs: Optional[Dict[str, Any]] = None,
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**kwargs: Dict[str, Any],
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) -> AgentExecutor:
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"""Construct a python agent from an LLM and tool."""
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tools = [tool]
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agent: BaseSingleActionAgent
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if agent_type == AgentType.ZERO_SHOT_REACT_DESCRIPTION:
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prompt = ZeroShotAgent.create_prompt(tools, prefix=prefix)
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llm_chain = LLMChain(
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llm=llm,
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prompt=prompt,
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callback_manager=callback_manager,
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)
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tool_names = [tool.name for tool in tools]
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agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs) # type: ignore[arg-type]
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elif agent_type == AgentType.OPENAI_FUNCTIONS:
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system_message = SystemMessage(content=prefix)
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_prompt = OpenAIFunctionsAgent.create_prompt(system_message=system_message)
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agent = OpenAIFunctionsAgent( # type: ignore[call-arg]
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llm=llm,
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prompt=_prompt,
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tools=tools,
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callback_manager=callback_manager,
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**kwargs, # type: ignore[arg-type]
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)
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else:
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raise ValueError(f"Agent type {agent_type} not supported at the moment.")
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return AgentExecutor.from_agent_and_tools(
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agent=agent,
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tools=tools,
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callback_manager=callback_manager,
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verbose=verbose,
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**(agent_executor_kwargs or {}),
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)
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